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Social Network Analytic-Based Online Counterfeit Seller Detection using User Shared Images

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Published:05 January 2023Publication History
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Abstract

Selling counterfeit online has become a serious problem, especially with the advancement of social media and mobile technology. Instead of investigating the products directly, one can only check the images, tags annotated by the sellers on the images, or the price to decide if a seller sells counterfeits. One of the ways to detect counterfeit sellers is to investigate their social graphs, in which counterfeit sellers show different behaviour in network measurements, such as those in centrality and EgoNet. However, social graphs are not easily accessible. They may be kept private by the operators, or there are no connections at all. This article proposes a framework to detect counterfeit sellers using their connection graphs discovered from their shared images. Based on 153 K shared images from Taobao, it is proven that counterfeit sellers have different network behaviours. It is observed that the network measurements follow Beta function well. Those distributions are formulated to detect counterfeit sellers by the proposed framework, which is 60% better than approaches using classification.

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          • Published in

            cover image ACM Transactions on Multimedia Computing, Communications, and Applications
            ACM Transactions on Multimedia Computing, Communications, and Applications  Volume 19, Issue 1
            January 2023
            505 pages
            ISSN:1551-6857
            EISSN:1551-6865
            DOI:10.1145/3572858
            • Editor:
            • Abdulmotaleb El Saddik
            Issue’s Table of Contents

            Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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            Publication History

            • Published: 5 January 2023
            • Online AM: 12 March 2022
            • Accepted: 6 March 2022
            • Revised: 3 December 2021
            • Received: 18 May 2021
            Published in tomm Volume 19, Issue 1

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